Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

Shashi Kumar,Satya P S Kushwaha,Prashant K Srivastava,Praveen K Thakur,Himanshu Govil

doi:10.3390/rs12244042

Abstract

Spaceborne and airborne polarimetric synthetic-aperture radar interferometry (PolInSAR) data have been extensively used for forest parameter retrieval. The PolInSAR models have proven their potential in the accurate measurement of forest vegetation height. Spaceborne monostatic multifrequency data of different SAR missions and the Global Ecosystem Dynamics Investigation (GEDI)-derived forest canopy height map were used in this study for vegetation height retrieval. This study tested the performance of PolInSAR complex coherence-based inversion models for estimating the vegetation height of the forest ranges of Doon Valley, Uttarakhand, India. The inversion-based forest height obtained from the three-stage inversion (TSI) model had higher accuracy than the coherence amplitude inversion (CAI) model-based estimates. The vegetation height values of GEDI-derived canopy height map did not show good relation with field-measured forest height values. It was found that, at several locations, GEDI-derived forest height values underestimated the vegetation height. The statistical analysis of the GEDI-derived estimates with field-measured height showed a high root mean square error (RMSE; 5.82 m) and standard error (SE; 5.33 m) with a very low coefficient of determination (R2; 0.0022). An analysis of the spaceborne-mission-based forest height values suggested that the L-band SAR has great potential in forest height retrieval. TSI-model-based forest height values showed lower p-values, which indicates the significant relation between modelled and field-measured forest height values. A comparison of the results obtained from different SAR systems is discussed, and it is observed that the L-band-based PolInSAR inversion gives the most reliable result with low RMSE (2.87 m) and relatively higher R2 (0.53) for the linear regression analysis between the modelled tree height and the field data. These results indicate that higher wavelength PolInSAR datasets are more suitable for tree canopy height estimation using the PolInSAR inversion technique.

Highlights

Spaceborne remote sensing technique is an important tool to measure different parameters of forest vegetation to understand the forest carbon fluxes for the modelling of gross primary production and net ecosystem production [1]
Forest heights generated from RADARSAT-2 and TerraSAR-X are shown in Figure 10a,b and Figure 11a,b, respectively
The Three-Stage Inversion (TSI) and coherence amplitude inversion (CAI) modelling approaches were implemented on monostatic PolInSAR data to generate forest height maps

Summary

Introduction

Spaceborne remote sensing technique is an important tool to measure different parameters of forest vegetation to understand the forest carbon fluxes for the modelling of gross primary production and net ecosystem production [1]. The recent loss of equilibrium of the Earth’s carbon cycle, mainly caused due to human activity, has likely triggered recent climate changes which could be harmful to the biosphere of the Earth [6,7,8]. Because of these reasons, accurate tracking and measures to achieve a better understanding of the Earth’s carbon cycle are very important for sustaining life. The height of the forest trees needs to be measured at regular intervals to understand the spatiotemporal changes in the aboveground biomass and carbon stock

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Results

Discussion

Conclusion